Radiomics capabilities in the interpretation of ultrasound and CT data in patients with chronic kidney disease: A review
The purpose of this review is to explore the possibilities of radiomics in interpreting ultrasound and multislice spiral computed tomography data in patients with chronic kidney disease (CKD). Radiomics is a promising area of medical image analysis based on the extraction of quantitative features no...
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| Format: | Article |
| Language: | Russian |
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"Consilium Medicum" Publishing house
2025-01-01
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| Series: | Терапевтический архив |
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| Online Access: | https://ter-arkhiv.ru/0040-3660/article/viewFile/677562/202484 |
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| author | Alexandra V. Proskura Khalil M. Ismailov Alexander G. Smoleevskiy Amina I. Salpagarova Irina N. Bobkova Andrei M. Shestiuk |
| author_facet | Alexandra V. Proskura Khalil M. Ismailov Alexander G. Smoleevskiy Amina I. Salpagarova Irina N. Bobkova Andrei M. Shestiuk |
| author_sort | Alexandra V. Proskura |
| collection | DOAJ |
| description | The purpose of this review is to explore the possibilities of radiomics in interpreting ultrasound and multislice spiral computed tomography data in patients with chronic kidney disease (CKD). Radiomics is a promising area of medical image analysis based on the extraction of quantitative features not available in standard visual analysis and the subsequent use of artificial intelligence methods for their processing and interpretation. The article discusses the basics of radiomic methods, including texture analysis of images and the creation of diagnostic models using machine learning algorithms. The advantages of radiomic characteristics, in particular statistical features of order II and higher orders, in assessing interstitial fibrosis and other abnormal changes in the renal parenchyma are discussed in detail. The results of studies demonstrating a strong correlation of radiomic signs with histological changes detected during kidney biopsy are presented. The prospects of radiomics as a non-invasive approach for assessing kidney damage and monitoring CKD progression are emphasized. The conclusion indicates the need for further research to standardize and expand the use of radiomic methods in clinical practice to improve the diagnosis accuracy and prognostic assessment of patients with CKD. |
| format | Article |
| id | doaj-art-2aed75da8eda481198e179d93de50be4 |
| institution | Kabale University |
| issn | 0040-3660 2309-5342 |
| language | Russian |
| publishDate | 2025-01-01 |
| publisher | "Consilium Medicum" Publishing house |
| record_format | Article |
| series | Терапевтический архив |
| spelling | doaj-art-2aed75da8eda481198e179d93de50be42025-08-20T03:44:28Zrus"Consilium Medicum" Publishing houseТерапевтический архив0040-36602309-53422025-01-0197650350810.26442/00403660.2025.06.20325978685Radiomics capabilities in the interpretation of ultrasound and CT data in patients with chronic kidney disease: A reviewAlexandra V. Proskura0https://orcid.org/0000-0003-0441-4799Khalil M. Ismailov1https://orcid.org/0000-0003-0548-190XAlexander G. Smoleevskiy2https://orcid.org/0000-0002-8771-8589Amina I. Salpagarova3https://orcid.org/0009-0006-9642-7202Irina N. Bobkova4https://orcid.org/0000-0002-8007-5680Andrei M. Shestiuk5https://orcid.org/0000-0002-2624-5773Sechenov First Moscow State Medical University (Sechenov University)Sechenov First Moscow State Medical University (Sechenov University)Sechenov First Moscow State Medical University (Sechenov University)Sechenov First Moscow State Medical University (Sechenov University)Sechenov First Moscow State Medical University (Sechenov University)Brest Regional Clinical HospitalThe purpose of this review is to explore the possibilities of radiomics in interpreting ultrasound and multislice spiral computed tomography data in patients with chronic kidney disease (CKD). Radiomics is a promising area of medical image analysis based on the extraction of quantitative features not available in standard visual analysis and the subsequent use of artificial intelligence methods for their processing and interpretation. The article discusses the basics of radiomic methods, including texture analysis of images and the creation of diagnostic models using machine learning algorithms. The advantages of radiomic characteristics, in particular statistical features of order II and higher orders, in assessing interstitial fibrosis and other abnormal changes in the renal parenchyma are discussed in detail. The results of studies demonstrating a strong correlation of radiomic signs with histological changes detected during kidney biopsy are presented. The prospects of radiomics as a non-invasive approach for assessing kidney damage and monitoring CKD progression are emphasized. The conclusion indicates the need for further research to standardize and expand the use of radiomic methods in clinical practice to improve the diagnosis accuracy and prognostic assessment of patients with CKD.https://ter-arkhiv.ru/0040-3660/article/viewFile/677562/202484radiomicschronic renal failurefibrosisartificial intelligencemedical decision support system |
| spellingShingle | Alexandra V. Proskura Khalil M. Ismailov Alexander G. Smoleevskiy Amina I. Salpagarova Irina N. Bobkova Andrei M. Shestiuk Radiomics capabilities in the interpretation of ultrasound and CT data in patients with chronic kidney disease: A review Терапевтический архив radiomics chronic renal failure fibrosis artificial intelligence medical decision support system |
| title | Radiomics capabilities in the interpretation of ultrasound and CT data in patients with chronic kidney disease: A review |
| title_full | Radiomics capabilities in the interpretation of ultrasound and CT data in patients with chronic kidney disease: A review |
| title_fullStr | Radiomics capabilities in the interpretation of ultrasound and CT data in patients with chronic kidney disease: A review |
| title_full_unstemmed | Radiomics capabilities in the interpretation of ultrasound and CT data in patients with chronic kidney disease: A review |
| title_short | Radiomics capabilities in the interpretation of ultrasound and CT data in patients with chronic kidney disease: A review |
| title_sort | radiomics capabilities in the interpretation of ultrasound and ct data in patients with chronic kidney disease a review |
| topic | radiomics chronic renal failure fibrosis artificial intelligence medical decision support system |
| url | https://ter-arkhiv.ru/0040-3660/article/viewFile/677562/202484 |
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